NhuanTDBK

import gradio as gr
import pandas as pd
import random


def get_random_data():
    return df.sample(10)


def display_data():

NhuanTDBK

import tensorflow_hub as hub
TFHUB_URL = "https://tfhub.dev/google/universal-sentence-encoder/2"
sentence_encoder = hub.Module(TFHUB_URL)    

NhuanTDBK

      val configJanus = new PropertiesConfiguration(configJanusPath)
      val graph = JanusGraphFactory.open(configJanus)
      // create schema
      val tx = graph.buildTransaction().enableBatchLoading().start()
      while (iter.hasNext) {
        val item = iter.next()
        val key = item.getString(0)
        val value = item.getString(1)

        val productVertex = tx.addVertex(T.label, NodeConstraint.PRODUCT_LABEL)

NhuanTDBK

graph = JanusGraphFactory.open("conf/gremlin-server/janusgraph-cql-es.properties")
mgmt = graph.openManagement()
mgmt.updateIndex(mgmt.getGraphIndex("ByShopIDAndRefID"), SchemaAction.REINDEX).get()
mgmt.updateIndex(mgmt.getGraphIndex("ByShopID"), SchemaAction.REINDEX).get()

NhuanTDBK

graph = JanusGraphFactory.open("conf/gremlin-server/janusgraph-cql-es.properties")

mgmt = graph.openManagement()
mgmt.makePropertyKey("shop_id").dataType(Long.class).cardinality(Cardinality.SINGLE).make()
mgmt.makePropertyKey("ref_id").dataType(Long.class).cardinality(Cardinality.SINGLE).make()
mgmt.commit()

mgmt = graph.openManagement()
shopID = mgmt.getPropertyKey("shop_id")
refId = mgmt.getPropertyKey("ref_id")

NhuanTDBK

map_col = lambda dat,col: col+"-"+dat.map(str)
gen_hash_item = lambda field, feat: '{0}:{1}:1'.format(field,hashstr(feat))
def gen_hash_row(feats,label):
    result = []
    for idx, item in enumerate(feats):
        val = item.split('-')[-1]
        if val != 'nan':
                result.append(gen_hash_item(idx,item))
    lbl = 1
    if label == 0:

NhuanTDBK

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console